Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Christopher Wesley Cleghorn"'
Publikováno v:
Information Sciences. 512:1043-1062
In high dimensional problem spaces, particle swarm optimization (PSO) is prone to unwanted roaming behaviour due to initial velocity explosion. A particle swarm’s movement patterns are strongly influenced by the inertia weight and acceleration coef
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d55cff1ee297215e289e7c75ccf6416
https://doi.org/10.1016/j.ins.2019.09.057
https://doi.org/10.1016/j.ins.2019.09.057
Publikováno v:
Swarm Intelligence. 13:245-276
This article presents a new particle swarm optimization (PSO)-based multi-objective optimization algorithm, named multi-guide particle swarm optimization (MGPSO). The MGPSO is a multi-swarm approach, where each subswarm optimizes one of the objective
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a2f3eeadecb0bec48715793961a70373
https://doi.org/10.1007/s11721-019-00171-0
https://doi.org/10.1007/s11721-019-00171-0
Publikováno v:
Swarm Intelligence. 13:193-215
This paper illustrates the importance of independent, component-wise stochastic scaling values, from both a theoretical and empirical perspective. It is shown that a swarm employing scalar stochasticity in the particle update equation is unable to ex
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::42c4b5a1cee5d442cd69b157ad04ce67
https://doi.org/10.1007/s11721-019-00168-9
https://doi.org/10.1007/s11721-019-00168-9
Publikováno v:
SSCI
The canonical particle swarm optimizer (PSO) is generally unsuitable for use in dynamic environments owing to its loss of diversity, the inability to detect changes in the environment, and the outdated memory of the particles’ previous positions fo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::91f965f417e779fc0646bb77845dfff0
https://doi.org/10.1109/ssci47803.2020.9308577
https://doi.org/10.1109/ssci47803.2020.9308577
Publikováno v:
CEC
A hyper-heuristic is an optimization approach that continually selects the most appropriate heuristic(s) to apply to an optimization problem. Hyper-heuristics conduct a search in the space of heuristics, or heuristic space, for the most suitable heur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eafd388feef657ca732bd0d3607c8e71
https://doi.org/10.1109/cec48606.2020.9185719
https://doi.org/10.1109/cec48606.2020.9185719
Publikováno v:
Swarm Intelligence. 12:1-22
This paper presents an extension of the state of the art theoretical model utilized for understanding the stability criteria of the particles in particle swarm optimization algorithms. Conditions for order-1 and order-2 stability are derived by model
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0128b42667108887222d151dc639e0a6
https://doi.org/10.1007/s11721-017-0141-x
https://doi.org/10.1007/s11721-017-0141-x
Autor:
Christopher Wesley Cleghorn
Publikováno v:
Applications of Evolutionary Computation ISBN: 9783030166915
EvoApplications
EvoApplications
This paper’s primary aim is to provide clarity on which guarantees about particle stability can actually be made. The particle swarm optimization algorithm has undergone a considerable amount of theoretical analysis. However, with this abundance of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8cb1e22d578efcdf5adaf74c07d534b8
https://doi.org/10.1007/978-3-030-16692-2_36
https://doi.org/10.1007/978-3-030-16692-2_36
Publikováno v:
GECCO (Companion)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6a70a3d42b99337d42f76529af7f1d56
https://doi.org/10.1145/3205651.3207877
https://doi.org/10.1145/3205651.3207877
Publikováno v:
Swarm Intelligence. 9:291-314
This article investigates various aspects of angle modulated particle swarm optimisers (AMPSO). Previous attempts at improving the algorithm have only been able to produce better results in a handful of test cases. With no clear understanding of when
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eaba97893d33c35a47af878daabe31da
https://doi.org/10.1007/s11721-015-0114-x
https://doi.org/10.1007/s11721-015-0114-x
Publikováno v:
Swarm Intelligence. 9:177-203
This paper presents an objective function specially designed for the convergence analysis of a number of particle swarm optimization (PSO) variants. It was found that using a specially designed objective function for convergence analysis is both a si
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::319a3304151f38dd847f734a668a1d07
https://doi.org/10.1007/s11721-015-0109-7
https://doi.org/10.1007/s11721-015-0109-7